Devops Engineer with AI

A DevOps Engineer with AI is commonly called an AI DevOps Engineer, MLOps Engineer, or DevOps Engineer - AI/ML Platforms, depending on the responsibilities.Chicago ILClient: CognizantHybridLife Science or Pharma domainKey SkillsDevOps: CI/CD, Jenkins, GitHub Actions, GitLab CI, Azure DevOpsCloud: AWS, Azure, GCPContainers: Docker, Kubernetes, OpenShiftIaC: Terraform, Ansible, CloudFormationAI/ML: MLOps, MLflow, Kubeflow, SageMaker, Azure MLAI/GenAI: LLMs, Generative AI, model deployment, inferenceProgramming: Python, Bash, PowerShellMonitoring: Prometheus, Grafana, ELK, DatadogAI Operations: Model monitoring, automated retraining, model versioning, GPU infrastructureTypical role: Build and automate the infrastructure, CI/CD pipelines, deployment, scaling, monitoring, and lifecycle management for AI/ML and Generative AI applications.A DevOps Engineer with AI is commonly called an AI DevOps Engineer, MLOps Engineer, or DevOps Engineer - AI/ML Platforms, depending on the responsibilities.Key SkillsDevOps: CI/CD, Jenkins, GitHub Actions, GitLab CI, Azure DevOpsCloud: AWS, Azure, GCPContainers: Docker, Kubernetes, OpenShiftIaC: Terraform, Ansible, CloudFormationAI/ML: MLOps, MLflow, Kubeflow, SageMaker, Azure MLAI/GenAI: LLMs, Generative AI, model deployment, inferenceProgramming: Python, Bash, PowerShellMonitoring: Prometheus, Grafana, ELK, DatadogAI Operations: Model monitoring, automated retraining, model versioning, GPU infrastructureTypical role: Build and automate the infrastructure, CI/CD pipelines, deployment, scaling, monitoring, and lifecycle management for AI/ML and Generative AI applications.